Basic stats

## [1] "number of species sampled:  149"
##                       sp     cmax        tL      bM1c     sDens      RcTh
## 1                        271.0000 239.07719 1.9846593 0.5117742 28.932225
## 2      Amaioua corymbosa 139.0000       NaN 1.6934338 0.5925926 37.992832
## 3     Amaioua guianensis 201.0000  10.37498 0.4327943 0.6222222  3.225806
## 4  Amphirrhox longifolia 173.4286  52.09969 0.8210011 0.5380701 44.337085
## 5 Anacardium parvifolium 244.1667  37.95601 2.9769794 0.5391994 35.520742
## 6          Aniba riparia 228.0000  32.13848 0.8081630 0.4212963 15.760870
##      RcPos        tL     taper       HGE      rgrBc      LIEc      LUEc
## 1 85.19111 239.07719 -3.925693 0.8446307 0.05308542 104.00511 -82.40488
## 2 87.45520       NaN -8.973132 0.8359817 0.25486161       NaN       NaN
## 3 99.41349  10.37498 -2.843502 2.2988816 0.07837783  23.97208  19.43178
## 4 80.10286  52.09969 -6.363875 1.6568296 0.21052631  59.90371  15.38360
## 5 87.45503  37.95601 -6.356338 1.0968644 0.16537511  27.43992  50.84863
## 6 88.85870  32.13848 -2.967233 1.5881993 0.09631796  39.76732  13.50955
##       cDens       cSh   Hmax
## 1  46.28419 0.5564862    NaN
## 2       NaN 0.6319444 17.015
## 3 259.93375 0.9428571 13.000
## 4  28.47908 0.7347767 13.225
## 5  54.22304 0.7435369 30.625
## 6  67.14093 0.4797297 15.700

Architecture: crown and stem

## Warning in xy.coords(x, y, xlabel, ylabel, log): 2 y values <= 0 omitted
## from logarithmic plot

Hmax

## Warning in xy.coords(x, y, xlabel, ylabel, log): 2 y values <= 0 omitted
## from logarithmic plot

PCA

## Importance of components:
##                           PC1    PC2    PC3     PC4     PC5     PC6
## Standard deviation     1.9178 1.3994 1.0869 0.89571 0.84625 0.72793
## Proportion of Variance 0.3851 0.2050 0.1237 0.08401 0.07499 0.05548
## Cumulative Proportion  0.3851 0.5901 0.7138 0.79786 0.87284 0.92833
##                            PC7     PC8     PC9    PC10      PC11
## Standard deviation     0.59481 0.44006 0.36295 0.07291 4.286e-16
## Proportion of Variance 0.03705 0.02028 0.01379 0.00056 0.000e+00
## Cumulative Proportion  0.96537 0.98565 0.99944 1.00000 1.000e+00

Partial regression

## 
## Call:
## lm(formula = log(tmp$cmax) ~ log(tmp$bM1c))
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.53869 -0.07594  0.01748  0.09333  0.33628 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    1.27963    0.01247 102.619   <2e-16 ***
## log(tmp$bM1c)  0.19317    0.02051   9.417   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.1507 on 145 degrees of freedom
## Multiple R-squared:  0.3795, Adjusted R-squared:  0.3752 
## F-statistic: 88.68 on 1 and 145 DF,  p-value: < 2.2e-16

## 
## Call:
## lm(formula = log(tmp$tL) ~ log(tmp$bM1c))
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -3.10781 -0.43079  0.08382  0.54073  1.34389 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    3.90241    0.06015  64.876  < 2e-16 ***
## log(tmp$bM1c)  0.75979    0.09895   7.678 2.19e-12 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.7269 on 145 degrees of freedom
## Multiple R-squared:  0.2891, Adjusted R-squared:  0.2842 
## F-statistic: 58.96 on 1 and 145 DF,  p-value: 2.189e-12

## 
## Call:
## lm(formula = lb$residuals ~ hb$residuals)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.94164 -0.49322  0.07839  0.53659  1.37778 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept)  1.356e-17  5.963e-02   0.000    1.000
## hb$residuals 5.035e-01  3.984e-01   1.264    0.208
## 
## Residual standard error: 0.723 on 145 degrees of freedom
## Multiple R-squared:  0.0109, Adjusted R-squared:  0.004075 
## F-statistic: 1.597 on 1 and 145 DF,  p-value: 0.2083

## 
## Call:
## lm(formula = log(tmp$rgrBc) ~ log(tmp$tL))
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1.84389 -0.18035  0.04198  0.29287  0.92595 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -2.56877    0.16078 -15.977  < 2e-16 ***
## log(tmp$tL)  0.14190    0.04061   3.494 0.000631 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.4216 on 145 degrees of freedom
## Multiple R-squared:  0.07766,    Adjusted R-squared:  0.0713 
## F-statistic: 12.21 on 1 and 145 DF,  p-value: 0.0006312

## 
## Call:
## lm(formula = gl$residuals ~ lb$residuals)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1.85965 -0.18655  0.04603  0.29705  0.94678 
## 
## Coefficients:
##                Estimate Std. Error t value Pr(>|t|)
## (Intercept)  -3.625e-17  3.475e-02   0.000    1.000
## lb$residuals -2.061e-02  4.814e-02  -0.428    0.669
## 
## Residual standard error: 0.4214 on 145 degrees of freedom
## Multiple R-squared:  0.001262,   Adjusted R-squared:  -0.005625 
## F-statistic: 0.1833 on 1 and 145 DF,  p-value: 0.6692

## 
## Call:
## lm(formula = hb2$residuals ~ tmp2$Hmax)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.55995 -0.08056  0.00781  0.06676  0.30982 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0079246  0.0396513  -0.200    0.842
## tmp2$Hmax    0.0004162  0.0019537   0.213    0.832
## 
## Residual standard error: 0.1289 on 86 degrees of freedom
## Multiple R-squared:  0.0005275,  Adjusted R-squared:  -0.01109 
## F-statistic: 0.04539 on 1 and 86 DF,  p-value: 0.8318
## 
## Call:
## lm(formula = lb2$residuals ~ tmp2$Hmax)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.09574 -0.37424  0.04807  0.46167  1.24531 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)  
## (Intercept)  0.38933    0.19462   2.000   0.0486 *
## tmp2$Hmax   -0.02045    0.00959  -2.132   0.0358 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.6325 on 86 degrees of freedom
## Multiple R-squared:  0.05022,    Adjusted R-squared:  0.03918 
## F-statistic: 4.548 on 1 and 86 DF,  p-value: 0.03582

## 
## Call:
## lm(formula = gl2$residuals ~ tmp2$Hmax)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.99518 -0.18479  0.03731  0.19710  0.82883 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.029470   0.099265  -0.297    0.767
## tmp2$Hmax    0.001548   0.004891   0.316    0.752
## 
## Residual standard error: 0.3226 on 86 degrees of freedom
## Multiple R-squared:  0.001163,   Adjusted R-squared:  -0.01045 
## F-statistic: 0.1002 on 1 and 86 DF,  p-value: 0.7524